Home / GPU Comparison / Intel Graphics 4 Xe-Cores (Panther Lake) or NVIDIA GeForce RTX 5060 Mobile: What's better?

Intel Graphics 4 Xe-Cores (Panther Lake)

vs

NVIDIA GeForce RTX 5060 Mobile

GPU Comparison Result

Below are the results of a comparison of Intel Graphics 4 Xe-Cores (Panther Lake) and NVIDIA GeForce RTX 5060 Mobile video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

Intel Graphics 4 Xe-Cores (Panther Lake)

Higher Boost Clock: 2300-2500 MHz (2300-2500 MHz vs 2520 MHz)
Newer Launch Date: January 2026 (January 2026 vs January 2025)

NVIDIA GeForce RTX 5060 Mobile

Larger Memory Size: 8GB (System Shared vs 8GB)
Higher Bandwidth: 80.00GB/s (System Dependent vs 80.00GB/s)
More Shading Units: 4608 (512 vs 4608)

Basic

Intel

Label Name

NVIDIA

January 2026

Launch Date

January 2025

Integrated

Platform

Desktop

Panther Lake

Former Codename

Intel 3

GPU Lithography

Intel Graphics

Model Name

GeForce RTX 5060 Mobile

Xe3 (Panther Lake)

Generation

GeForce 50 Mobile

300 MHz

Base Clock

2235 MHz

2300-2500 MHz

Boost Clock

2520 MHz

Bus Interface

PCIe 5.0 x16

Transistors

Unknown

RT Cores

Tensor Cores

Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.

144

TMUs

Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.

144

Intel

Foundry

TSMC

Intel 3

Process Size

Xe3

Architecture

Blackwell 2.0

Xe-cores

Memory Specifications

System Shared

Memory Size

8GB

DDR5 / LPDDR5X (System Shared)

Memory Type

GDDR7

System Shared

Memory Bus

The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.

128bit

System Dependent

Memory Clock

2500 MHz

System Dependent

Bandwidth

Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.

80.00GB/s

Display and Media

Yes

AV1 Encode/Decode

DisplayPort 2.1 UHBR20

DisplayPort Extensions

Yes

H.264 Hardware Encode/Decode

Yes

H.265 HEVC Hardware Encode/Decode

Decode Only

H.266 VVC Hardware Encode/Decode

HDMI 2.1 FRL

HDMI Version

Yes

Intel Quick Sync Video

7680 x 4320 @ 60Hz

Max Resolution DP

3840 x 2400 @ 120Hz

Max Resolution eDP

Number of Displays Supported

eDP 1.5, DisplayPort 2.1 UHBR20, HDMI 2.1 FRL

Outputs

1x HDMI 2.1
3x DisplayPort 1.4a

Theoretical Performance

36.8-40.0 GPixel/s

Pixel Rate

Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.

121.0 GPixel/s

73.6-80.0 GTexel/s

Texture Rate

Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.

362.9 GTexel/s

FP16 (half)

An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.

23.22 TFLOPS

FP64 (double)

An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.

362.9 GFLOPS

2.56 TFLOPS

FP32 (float)

An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.

22.756 TFLOPS

AI Features

OpenVINO, WindowsML, DirectML, ONNX RT, WebGPU, WebNN

AI Software Frameworks Supported by GPU

37-40 TOPS

GPU Peak TOPS (Int8)

Yes

Intel Deep Learning Boost on GPU

Miscellaneous

SM Count

Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.

512

Shading Units

The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.

4608

L1 Cache

128 KB (per SM)

4 MB

L2 Cache

32 MB

TDP

120W

1.4

Vulkan Version

Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.

1.3

3.0

OpenCL Version

3.0

4.6

OpenGL

4.6

CUDA

9.1

DirectX 12 Ultimate

DirectX

12 Ultimate (12_2)

Power Connectors

1x 16-pin

ROPs

The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.

Shader Model

6.8

Suggested PSU

300 W